With the increasingly wide use of data and messaging networks for transmitting data has come an increased demand on communications networks and network platforms. Similarly, the inclusion of an increasing number of data and messaging applications on communications devices has further increased demand on communications networks. For example, the proliferation of wireless data transfer has been accompanied by a corresponding increase in wireless network requirements.
Wireless communications networks typically consist of hundreds of interconnected platforms. Maintaining network resource availability for the ever-increasing resource demand is a complex task. Aside from the difficulty in identifying and tracking a current network configuration for a complex network, planning for future network configurations can be an extremely complex task. The enormous amount of data that must be collected, analyzed, and considered, for example, current and future resource loads, pending network configuration changes, reconfigurations required to support growing subscriber loads, upgrades in resource capabilities, and the like, makes future network planning difficult.
Traditionally, network planning has been performed through manual manipulation of network data by network personnel. The capacity of this type of planning is often limited to a portion of the network. Furthermore, different personnel may perform analysis of various portions of the network according to varied methods, resulting in an increased likelihood of error and a decreased likelihood of “big-picture” planning. Compounding these difficulties is the fact that marketing and/or product-driven changes may not be properly taken into account during any network utilization analysis since such data is rarely, if ever, in the hands of the personnel performing such analysis.